Senior Product Ops Specialist (Giant Robot Lab)
GovTech Singapore is hiring a Senior Product Ops Specialist (Giant Robot Lab) in Singapore, Singapore. Level rates it ; you can apply on GovTech Singapore.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- The posting mentions Claude, Claude Code and Codex among its tools and skills.
- Level classes it as a senior role.
- GovTech Singapore has 257 other open roles on Level.
- Posted within the past two weeks.
AI in this role
GovTech is the lead agency driving Singapore’s Smart Nation initiatives and public sector digital transformation. As the Centre of Excellence for Infocomm Technology and Smart Systems (ICT & SS), GovTech develops the Singapore Government’s capabilities in Data Science & Artificial Intelligence, Application Development, Smart City Technology, Digital Infrastructure, and Cybersecurity.
At GovTech, we offer you a purposeful career to make lives better where we empower our people to master their craft through robust learning and development opportunities all year round.
Play a part in Singapore’s vision to build a Smart Nation and embark on your meaningful journey to build tech for public good. Join us to advance our mission and shape your future with us today!
Learn more about GovTech at tech.gov.sg.
[About Giant Robots Labs]
Giant Robots Labs is the experimental technology lab inside GovTech's Government Technology Office. We turn ambitious ideas into working products quickly, test them with real users, and operate the promising ones through prototype and limited beta. We also experiment with the lab itself: how small teams are organised, how software gets built when agents do much of the work, and what a product operation needs to look like when a pilot can reach real users in weeks.
Product operations usually exists because coordination, documentation and reporting are expensive manual work. Much of that work is now automatable, and we would rather automate it than staff it. So this is not a role that administers a process, maintains a backlog on someone else's behalf, or turns status into slides. It is the role that makes the lab run: deciding which problems become pilots, clearing the unglamorous path that stands between a working prototype and a real government user, and making sure we can tell whether any of it worked.
[What you will be working on]
- Run pilot intake. Help decide which problems become pilots, what question each pilot is actually testing, and when it has been answered.
- Clear the path to real users. Data sharing, security and classification review, agency sponsorship, accounts and access: a pilot team should spend its weeks building, not waiting.
- Own the operational side of limited beta, including user onboarding and support, incident response, cost and quality monitoring, and the dull reliability work that decides whether an agency trusts us with the next thing.
- Instrument pilots so that continue-or-kill decisions rest on usage and evidence rather than on who argues hardest.
- Keep the lab's context legible. Decisions, hypotheses, results and abandoned approaches, recorded in a form that both people and agents can read and act on.
- Build the lab's internal tooling and automation, agentic where that is the right answer, for the coordination and reporting work that would otherwise eat a team's attention. Where you can build it yourself, build it.
- Design the lab's ways of working, keep them light, and retire them when they stop earning their keep.
- Hold the GovTech interfaces: platform teams, identity, data infrastructure, procurement, legal, security. Know who answers which question, and be owed enough favours that the answer arrives in a day.
- Prepare successful pilots for what comes next, with the evidence, runbook, cost picture and open risks that a productisation team needs in order to pick one up.
- Notice when a pilot is drifting. No users, an untestable hypothesis, a prototype quietly becoming a system somebody has to run forever. Raise it early, including when nobody wants to hear it.
- Run the lab's own measurement. How fast pilots move, how many reach real users, what they cost to operate, and which of our decisions turned out to be wrong.
- Help new people and new teams get productive, which in a lab like this means tools and context more than induction decks.
- Experiment with the organisation itself. Team shapes, role boundaries, where agents sit in a team, and an honest read on whether last quarter's experiment worked.
- You would rather build or automate an operation than administer one, and you reach for a script, a workflow or an agent before a recurring meeting.
- You are comfortable that the process does not exist yet and that part of your job is deciding how little of it we need.
- You enjoy the unglamorous blockers. Approvals, access, classification, procurement and support are where pilots quietly die, and you find it satisfying to kill those delays permanently rather than route around them each time.
- You can hold an opinion about whether a product is working, and defend it with evidence in a room full of people who built it.
- You are willing to say that a pilot should stop.
- You work comfortably with engineers and designers as a peer rather than as coordination between them.
- You are hands-on with AI tools and curious about what they make unnecessary, including parts of your own job.
- You are energised by lean teams, broad ownership and problems that change shape every few months.
[What we are looking for]
- Around 5 to 8 years in product operations, programme or product management, business operations, delivery or a similar role, in an environment where software actually shipped.
- Evidence you have built or materially changed how a team works, rather than maintained how it already worked. We will ask what you introduced, what you removed, and how you knew which was which.
- Comfort with data. You can get to the numbers yourself, through SQL, spreadsheets, a BI tool or an analytics stack, and you know the difference between a metric that drives a decision and one that decorates a report.
- Technical fluency sufficient to work closely with engineers: you can read a system diagram, follow a deployment, understand what an API or an integration implies, and automate your own work.
- Practical fluency with AI tools, including agentic ones such as Claude Code, Codex or equivalents, and interest in using them to replace operational toil.
- Clear writing. Much of this role is making a decision, a risk or a result legible to people who were not in the room.
- A track record of high agency: things that happened because you decided they should.
What you can expect
- A role defined by what the lab needs rather than by a fixed set of artefacts to produce.
- Direct access to users, agency partners, stakeholders and decision-makers, with no brief passed down a chain.
- Real influence over which pilots start, continue and stop.
- Freedom to automate your own work, and to argue that a practice is not worth keeping.
- A wide variety of problems and domains across the Singapore public sector.
- A lab that is willing to change how it organises itself based on evidence, including evidence that you gather.
- Colleagues who own products end to end, and who will expect the same standard of ownership from you.
What we offer you:
GovTech is an equal opportunity employer committed to fostering an inclusive workplace that values diverse voices and perspectives, as we believe that diversity is the foundation to innovation.
Our employee benefits are based on a total rewards approach, offering a holistic and market-competitive suite of perks. These include leave benefits to meet your work-life needs and employee wellness programs.
We champion flexible work arrangements (subject to your job role) and trust that you will manage your own time to deliver your best, wherever you are, and whatever works best for you.
Learn more about life inside GovTech at go.gov.sg/GovTechCareers.
Stay connected with us on social media at go.gov.sg/ConnectWithGovTech
How we rate this
Senior Product Ops Specialist (Giant Robot Lab) at GovTech Singapore rates 63 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used Claude hands-on?
- Walk me through how you've used Claude Code in your day-to-day work.
- What are the limits of Codex that you've run into, and how did you work around them?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Claude, Claude Code, and Codex. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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